{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Temporal Convolution Network (TCN) for predictive maintenance of aircraft engines"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data\n",
    "Use the `TurboFan` class in `datasets.turbofan` to download and pre-process the turbofan dataset.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# add aidc-2018-timeseries to notebook path\n",
    "import sys\n",
    "sys.path.append(\"../\")\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading data\n",
      "Creating sliding window data\n",
      "Done. Number of samples in train: 160854, number of samples in test: 707\n"
     ]
    }
   ],
   "source": [
    "from datasets.turbofan import TurboFan\n",
    "\n",
    "# dataset configuration\n",
    "data_dir = \"./\"  # Location to download data to\n",
    "seq_len = 50     # Sequence length of samples in final processed dataset\n",
    "skip = 1         # Number of time-points between adjacent windows\n",
    "max_rul = 130    # Value at which the 'y' variable is capped\n",
    "\n",
    "# create dataset\n",
    "turbofan_dataset = TurboFan(data_dir=data_dir, T=seq_len, skip=skip, max_rul_predictable=max_rul,\n",
    "                            recurrent_axis_name='W', feature_axis_name='C', label_axis_name='Fo')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Call the `plot_sample` method of the dataset object to visualize a sample set of readings from the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x1440 with 24 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "out_folder = \"./\"  # Folder to write images to\n",
    "turbofan_dataset.plot_sample(out_folder, trajectory_id=10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create a data loader in ngraph-neon"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "from ngraph.frontends.neon import ArrayIterator\n",
    "\n",
    "batch_size = 128\n",
    "num_iterations = 10000\n",
    "\n",
    "train_iterator = ArrayIterator(turbofan_dataset.train,\n",
    "                               batch_size,\n",
    "                               total_iterations=num_iterations,\n",
    "                               shuffle=True)\n",
    "val_iterator = ArrayIterator(turbofan_dataset.test, batch_size)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Define placeholders\n",
    "First, we need to define placeholders; these will be used to feed data into the model in batches.\n",
    "`Axes` are a unique feature of ngraph; they are composed of `Axis` objects which are named dimensions that are matched by name instead of by ordering.\n",
    "Individual `Axis` can be named arbitrarily, though ngraph provides conventions for the batch axis (`'N'`) as \n",
    "well as the time axis in recurrent models and channel and spatial axes in convolutional models.\n",
    "\n",
    "\n",
    "(Typically, the time axis in ngraph is called `'REC'` (recurrent) but because we are using a convolutional model\n",
    "to process time series data, the time axis maps to the `'W'` axis, and the feature axis corresponds to `'C'`, the\n",
    "convolution channels.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import ngraph as ng\n",
    "\n",
    "# number of input and output features  \n",
    "n_features = turbofan_dataset.train['X']['data'].shape[2] # read off the number of features in the input data\n",
    "n_output_features = 1\n",
    "\n",
    "# name and create axes\n",
    "batch_axis = ng.make_axis(length=batch_size, name=\"N\")\n",
    "time_axis = ng.make_axis(length=seq_len, name=\"W\")\n",
    "feature_axis = ng.make_axis(length=n_features, name=\"C\")\n",
    "out_axis = ng.make_axis(length=n_output_features, name=\"Fo\")\n",
    "\n",
    "in_axes = ng.make_axes([batch_axis, time_axis, feature_axis])\n",
    "out_axes = ng.make_axes([batch_axis, out_axis])\n",
    "\n",
    "# build placeholders for the created axes\n",
    "inputs = dict(X=ng.placeholder(in_axes), \n",
    "              y=ng.placeholder(out_axes))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Build TCN Model\n",
    "\n",
    "The TCN model consists of residual blocks of which contain dilated convolutional layers, weight normalization, relu activations, and spatial dropout. Let's build a model with a single residual block."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<table class=\"image\">\n",
    "<caption align=\"bottom\">Residual block</caption>\n",
    "<tr><img src='img/residual_block.png' alt='residual block' width='250'></tr></table>\n",
    "\n",
    "Bai et al \"An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's first build the main path of the residual block. \n",
    "We create two convolution and dropout layers, and wrap them in a `Sequential` container.\n",
    "`Sequential` takes a list of neon layers or callables. [termininology]\n",
    "Calling a `Sequential` object will cause each of the layers to be called in order."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from topologies.custom_neon_classes import Dropout2D, DilatedCausalConv\n",
    "from ngraph.frontends.neon import GaussianInit, Rectlin, Sequential\n",
    "\n",
    "kernel_size = 5  # conv kernel size\n",
    "n_filters = 50   # number of filters per conv layer\n",
    "dilation = 1     # conv dilation\n",
    "dropout = 0.2    # dropout rate\n",
    "keep = 1 - dropout  # ratio to keep\n",
    "\n",
    "layers = []\n",
    "\n",
    "for i in range(2):\n",
    "    \n",
    "    # causal conv, weight norm, relu\n",
    "    layers += [DilatedCausalConv(filter_shape=(kernel_size, n_filters),\n",
    "                                 padding='causal',\n",
    "                                 dilation=dilation,\n",
    "                                 strides=1,\n",
    "                                 activation=Rectlin(),\n",
    "                                 filter_init=GaussianInit(0, 0.01), \n",
    "                                 batch_norm=False)]\n",
    "\n",
    "    # spatial dropout\n",
    "    layers += [Dropout2D(keep)]\n",
    "\n",
    "# combine layers in a Sequential container\n",
    "main_path = Sequential(layers)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now for the side path: this is the residual path. \n",
    "If the number of input channels and output channels of the main path are the same, the residual path passes the input, unmodified, to be added to the output of the main path.\n",
    "Otherwise, it uses 1-dimensional convolutions to ensure that the main and residual paths have the same number of output channels (`n_filters`)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "from ngraph.frontends.neon import Convolution\n",
    "\n",
    "side_path = Sequential([Convolution(filter_shape=(1, n_filters),\n",
    "                                    filter_init=GaussianInit(0, 0.01),\n",
    "                                    strides=1,\n",
    "                                    dilation=1,\n",
    "                                    padding='same',\n",
    "                                    batch_norm=False)])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Bring the two paths together using the `ResidualModule` API:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "from ngraph.frontends.neon.model import ResidualModule\n",
    "\n",
    "res_block = ResidualModule(main_path, side_path)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can combine the code from the last three cells into a factory function that creates residual blocks:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "from ngraph.frontends.neon import Convolution\n",
    "from ngraph.frontends.neon import GaussianInit, Rectlin, Sequential\n",
    "from ngraph.frontends.neon.model import ResidualModule\n",
    "from topologies.custom_neon_classes import Dropout2D, DilatedCausalConv\n",
    "\n",
    "\n",
    "def residual_block(kernel_size, n_filters, dilation, dropout, res_path_conv=False):\n",
    "\n",
    "    keep = 1 - dropout\n",
    "    \n",
    "    # main path\n",
    "    layers = []\n",
    "    for i in range(2):\n",
    "\n",
    "        # causal conv, weight norm, relu\n",
    "        layers += [DilatedCausalConv(filter_shape=(kernel_size, n_filters),\n",
    "                                     padding='causal',\n",
    "                                     dilation=dilation,\n",
    "                                     strides=1,\n",
    "                                     activation=Rectlin(),\n",
    "                                     filter_init=GaussianInit(0, 0.01), \n",
    "                                     batch_norm=False)]\n",
    "\n",
    "        # spatial dropout  \n",
    "        layers += [Dropout2D(keep)]\n",
    "\n",
    "    # combine layers in a Sequential container\n",
    "    main_path = Sequential(layers)\n",
    "    \n",
    "    # side path\n",
    "    if res_path_conv:\n",
    "        side_path = Sequential([Convolution(filter_shape=(1, n_filters),\n",
    "                                            filter_init=GaussianInit(0, 0.01),\n",
    "                                            strides=1,\n",
    "                                            dilation=1,\n",
    "                                            padding='same',\n",
    "                                            batch_norm=False)])\n",
    "    else:\n",
    "        side_path = None\n",
    "        \n",
    "    # residual block\n",
    "    res_block = ResidualModule(main_path, side_path)\n",
    "    \n",
    "    return res_block"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now build a TCN with a stack of residual blocks, where the convolutional layers in each block have the same number of filters. The first residual block will have 1-D convolutions in the residual path but the subsequent blocks will will not. Here we define the TCN layers:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "kernel_size = 4  # conv kernel size\n",
    "n_filters = 50   # number of filters per conv layer\n",
    "dropout = 0.1    # dropout rate\n",
    "\n",
    "num_blocks = 4   # number of residual blocks\n",
    "\n",
    "layers = []\n",
    "for i in range(num_blocks):\n",
    "    \n",
    "    dilation = 2 ** i\n",
    "    \n",
    "    res_path_conv = True if i == 0 else False\n",
    "    layers += [residual_block(kernel_size, n_filters, dilation, dropout, res_path_conv)]\n",
    "    layers += [Rectlin()]\n",
    "        \n",
    "tcn = Sequential(layers)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that the output of the TCN has the same sequence length as its input; \n",
    "however due to dilation of the convolution filters, the \"receptive field\" of each time-point in the output is much larger. \n",
    "Each time-point operates on multiple past time-points. \n",
    "If the network is deep enough, the last time-point has sufficiently large receptive field that its use alone will suffice to generate the output. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<table class=\"image\">\n",
    "<caption>Dilated convolution (3 layers)</caption>\n",
    "<tr><img src='img/dilated_conv.png' alt='dilated convolution' height='120'></tr></table>\n",
    "\n",
    "Bai et al \"An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can read off the last time-point as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "def last_timepoint(op):\n",
    "    # select the last timepoint of the Axis named \"W\"\n",
    "    slices = [slice(seq_len-1, seq_len, 1) if ax.name == \"W\" else slice(None) for ax in op.axes]\n",
    "    return ng.tensor_slice(op, slices)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Use an `Affine` layer to predict the RUL from the last time-point:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "from ngraph.frontends.neon.layer import Affine\n",
    "\n",
    "affine_layer = Affine(axes=out_axis, weight_init=GaussianInit(0, 0.01), activation=Rectlin())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, encapsulate the entire model in a `Sequential` container. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = Sequential([tcn, \n",
    "                    last_timepoint, \n",
    "                    affine_layer])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Specify training loss, validation loss, and optimizer"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Forward propagation through the defined model, on the input placeholder defined above:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "prediction_train = model(inputs['X'])  # model output"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Define the training loss as the Mean Squared Error (MSE) between model output `y_hat` and label placeholder:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_loss = ng.squared_L2(prediction_train - inputs['y'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Similarly, with `Layer.inference_mode_on()`, define the MSE for validation data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "from ngraph.frontends.neon import Layer\n",
    "\n",
    "with Layer.inference_mode_on():\n",
    "    prediction_val = model(inputs['X'])\n",
    "    \n",
    "eval_loss = ng.mean(ng.squared_L2(prediction_val - inputs['y']), out_axes=())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Define the optimizer:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "from ngraph.frontends.neon import Adam\n",
    "\n",
    "lr = 0.002                # learning rate\n",
    "grad_clip_value = 0.4     # gradient clip value\n",
    "\n",
    "optimizer = Adam(learning_rate=lr, gradient_clip_value=grad_clip_value)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we call the `optimizer`, which causes gradients to be computed and trainable parameters to be updated. \n",
    "We also compute the average minibatch training loss. \n",
    "Note that these two operations are combined into a single, ordered operation using `ng.sequential`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "batch_cost = ng.sequential([optimizer(train_loss), \n",
    "                            ng.mean(train_loss, out_axes=())])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create the train and validation computations:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_computation = ng.computation(batch_cost, \"all\") \n",
    "eval_computation = ng.computation(eval_loss, \"all\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Tensorboard visualization"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ngraph supports Tensorboard for visualization. \n",
    "The code below will cause a directory `tensorboard` to be created in the current directory,\n",
    "and a subdirectory within `tensorboard` named with the current timestamp, e.g. `180521T170237`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "from ngraph.op_graph.tensorboard.tensorboard import TensorBoard\n",
    "\n",
    "tensorboard_dir = \"./tensorboard/\"  # directory to save tensorboard summaries to\n",
    "\n",
    "# create tensorboard object \n",
    "tb = TensorBoard(tensorboard_dir)\n",
    "\n",
    "# add model graph for visualization\n",
    "tb.add_graph(model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To start tensorboard open a terminal and type the commands below.\n",
    "(Remember to replace the timestamp directory name with what you see in the local `tensorboard` directory.)\n",
    "Open a browser window and navigate to the URL printed in the terminal."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```\n",
    "cd aidc-2918-timeseries\n",
    ". .venv/bin/activate\n",
    "tensorboard --logdir=./tutorials/tensorboard/180521T170237\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Training the model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, model training:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100 Train Loss: 2668.38, Validation Loss: 1974.23\n",
      "200 Train Loss: 2086.71, Validation Loss: 2388.20\n",
      "300 Train Loss: 1790.47, Validation Loss: 2261.98\n",
      "400 Train Loss: 1606.36, Validation Loss: 1802.33\n",
      "500 Train Loss: 2552.10, Validation Loss: 2871.47\n",
      "600 Train Loss: 1491.04, Validation Loss: 1446.06\n",
      "700 Train Loss: 1604.33, Validation Loss: 1497.96\n",
      "800 Train Loss: 1523.82, Validation Loss: 1383.53\n",
      "900 Train Loss: 2305.86, Validation Loss: 1618.38\n",
      "1000 Train Loss: 2095.87, Validation Loss: 1579.24\n",
      "1100 Train Loss: 1461.98, Validation Loss: 1359.95\n"
     ]
    }
   ],
   "source": [
    "import ngraph.transformers as ngt\n",
    "from contextlib import closing\n",
    "\n",
    "train_iterator.reset()  # not necessary the first time train loop is run\n",
    "\n",
    "# Now bind the computations we are interested in\n",
    "with closing(ngt.make_transformer()) as transformer:\n",
    "    \n",
    "    # compile computations\n",
    "    train_function = transformer.add_computation(train_computation)\n",
    "    eval_function = transformer.add_computation(eval_computation)\n",
    "    \n",
    "    # train loop\n",
    "    for step, data in enumerate(train_iterator):\n",
    "\n",
    "        # construct feed dictionary of inputs to train function\n",
    "        feed_dict = {inputs[\"X\"]: data[\"X\"], inputs[\"y\"]: data[\"y\"]}\n",
    "        \n",
    "        # Mean batch cost\n",
    "        output = train_function(feed_dict=feed_dict)\n",
    "        train_loss = output[()].item()\n",
    "        tb.add_scalar(\"train_loss\", train_loss, step=step)\n",
    "        \n",
    "        # Every N iterations print test set metrics\n",
    "        if step % 100 == 0 and step > 0:\n",
    "\n",
    "            # calculate metrics over test set\n",
    "            avg_eval_loss = 0.0\n",
    "            val_iterator.reset()\n",
    "            for e, data_test in enumerate(val_iterator):\n",
    "                feed_dict_test = {inputs[\"X\"]: data_test[\"X\"], inputs[\"y\"]: data_test[\"y\"]}\n",
    "                eval_loss = eval_function(feed_dict=feed_dict_test)\n",
    "                avg_eval_loss += eval_loss\n",
    "\n",
    "            avg_eval_loss /= (e + 1)\n",
    "            tb.add_scalar(\"eval_loss\", avg_eval_loss, step=step)\n",
    "            \n",
    "            print(\"%d Train Loss: %4.2f, Validation Loss: %4.2f\" % (step, train_loss, avg_eval_loss))"
   ]
  }
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